We survey basic garbage collection algorithms, and variations such as incremental and generational collection; we then discuss low-level implementation considerations and the relationships between storage management systems, languages, and compilers. Throughout, we attempt to present a uni ed view based on abstract traversal strategies, addressing issues of conservatism, opportunism, and immediacy of reclamation; we also point outavariety of implementation details that are likely to have a significant impact on performance.

Much research has been devoted to studies of and algorithms for memory management based on garbage collection or explicit allocation and deallocation. An alternative approach, region-based memory management, has been known for decades, but has not been wellstudied. In a region-based system each allocation specifies a region, and memory is reclaimed by destroying a region, freeing all the storage allocated therein. We show that on a suite of allocation-intensive C programs, regions are competitive with malloc/free and sometimes substantially faster. We also show that regions support safe memory management with low overhead. Experience with our benchmarks suggests that modifying many existing programs to use regions is not difficult. 1 Introduction The two most popular memory management techniques are explicit allocation and deallocation, as in C's malloc/free, and various forms of garbagecollection [Wil92]. Both have well-known advantages and disadvantages, discussed further below. A t...

This paper introduces a copying garbage collection algorithm which is able to compact most of the accessible storage in the heap without having an explicitly defined set of pointers that contain the roots of all accessible storage. Using "hints" found in the processor's registers and stack, the algorithm is able to divide heap allocated objects into two groups: those that might be referenced by a pointer in the stack or registers, and those that are not. The objects which might be referenced are left in place, and the other objects are copied into a more compact representation. A Lisp compiler and runtime system which uses such a collector need not have complete control of the processor in order to force a certain discipline on the stack and registers. A Scheme implementation has been done for the Digital WRL Titan processor which uses a garbage collector based on this "mostly copying" algorithm. Like other languages for the Titan, it uses the Mahler intermediate language as its targe...

Region-based memory management systems structure memory by grouping objects in regions under program control. Memory is reclaimed by deleting regions, freeing all objects stored therein. Our compiler for C with regions, RC, prevents unsafe region deletions by keeping a count of references to each region. Using type annotations that make the structure of a program's regions more explicit, we reduce the overhead of reference counting from a maximum of 27% to a maximum of 11% on a suite of realistic benchmarks. We generalise these annotations in a region type system whose main novelty is the use of existentially quantified abstract regions to represent pointers to objects whose region is partially or totally unknown. A distribution of RC is available at http://www.cs.berkeley.edu/~dgay/rc.tar.gz.

The complexity of systems for automatic control and other safety-critical applications grows rapidly. Computer software represents an increasing part of the complexity. As larger systems are developed, we need to find scalable techniques to manage the complexity in order to guarantee high product quality. Memory management is a key quality factor for these systems. Automatic memory management, or garbage collection, is a technique that significantly reduces the complex problem of correct memory management. The risk of software errors decreases and development time is reduced. Garbage collection techniques suitable for interactive and soft real-time systems exist, but few approaches are suitable for systems with hard real-time requirements, such as control systems (embedded systems). One part of the problem is solved by incremental garbage collection algorithms, which have been presented before. We focus on the scheduling problem which forms the second part of the problem, i.e. how the work of a garbage collector should be scheduled in order

The deployment of Java as a concurrent programming language has created a critical need for high-performance, concurrent, and incremental multiprocessor garbage collection. We present the Recycler, a fully concurrent pure reference counting garbage collector that we have implemented in the Jalapeno Java virtual machine running on shared memory multiprocessors.

Abstract. Automatic storage reclamation via reference counting has important advantages, but has always suffered from a major weakness due to its inability to reclaim cyclic data structures. We describe a novel cycle collection algorithm that is both concurrent — it is capable of collecting garbage even in the presence of simultaneous mutation — and localized — it never needs to perform a global search of the entire data space. We describe our algorithm in detail and present a proof of correctness. We have implemented our algorithm in the Jalapeño Java virtual machine as part of the Recycler, a concurrent multiprocessor reference counting garbage collector that achieves maximum mutator pause times of only 6 milliseconds. We present measurements of the behavior of the cycle collection algorithm over a set of eight benchmarks that demonstrate the effectiveness of the algorithm at finding garbage cycles, handling concurrent mutation, and eliminating global tracing. 1

Weighted Reference Counting is a low communication distributed storage reclamation scheme for loosely-couple multiprocessors. The algorithm we present herein extends weighted reference counting to allow the collection of cyclic data structures. To do so, the algorithm identifies candidate objects that may be part of cycles and performs a tricolour mark-scan on their subgraph in a lazy manner to discover whether the subgraph is still in use. The algorithm is concurrent in the sense that multiple useful computation processes and garbage collection processes can be performed simultaneously. Keywords: Memory management, Distributed memory, Reference counting, Garbage collection. Introduction Computation on distributed systems involving several processors is already a reality. In a distributed multiprocessor system each processor is responsible for allocating and reclaiming structures residing in its local memory; interprocessor communication is far less efficient than local memory access...

Existing techniques for garbage collection and machine code optimizations can interfere with each other. The inability to fully optimize code in a garbage-collected system is a hidden cost of garbage collection. One solution to this problem is proposed; an inexpensive protocol that permits most optimizations and garbage collection to coexist. A second approach to this problem and a separate problem in its own right is to reduce the need for garbage collection. This requires analysis of storage lifetime. Inferring storage lifetime is di#cult in a language with nested and recursive data structures, but it is precisely these languages in which garbage collection is most useful. An improved analysis for "storage containment" is described. Containment information can be represented in a directed graph. The derivation of this graph falls into a monotone data-flow analysis framework; in addition, the derivation has the Church-Rosser property. The graphs produced in the analysis of a value-a...

We present CCount, a small extension to C that dynamically verifies the correctness of manual memory management using reference counting. CCount relies on a simple extension to the usual malloc/free memory management API, delayed free scopes during which otherwise dangling references can exist. Porting programs to CCount typically requires little effort (on average 0.56 % of lines change), adds an average 11 % time overhead (85 % in the worst case), and increases space usage by an average of 14%. These results are based on porting over half a million lines of C code, including perl where we found six previously unknown bugs. Many existing C programs continue to use unchecked manual memory management. One reason is that programmers fear that moving to garbage collection is too big a risk. We believe that CCount is a practical way to provide safe memory management for such programs. Since CCount checks existing memory management rather than changing it, programmers need not worry that CCount will introduce new bugs; and, since CCount does not manage memory itself, programmers can choose to deploy their programs without CCount if performance is critical (a simple header file allows CCount programs to compile and run with a regular C compiler). In contrast, we found that garbage collection, although faster, had much higher space overhead, and occasionally caused a space-usage explosion that made the program unusable. 1.